ArticleClinical rheumatology2026
Spatiotemporal trends and socioeconomic drivers of hip-knee osteoarthritis burden in East Asia: a GBD-based modeling study (1990-2023).
Article in Clinical rheumatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundAgainst the backdrop of population aging (over 29% of Japan's population aged 65 and above) and urbanization (regional urbanization rate rising from 38.5 to 67.3%) in East Asia, the socioeconomic driving mechanism of the disease burden of hip and knee osteoarthritis (OA) remains unclear.
objectiveA systematic analysis was conducted to examine the evolving trends in the disease burden of hip and knee OA in East Asia (including China, Japan, South Korea, Mongolia, and North Korea) from 1990 to 2023, as well as its associations with socioeconomic factors, to provide a basis for public health policies.
methodsBased on the 2023 edition of the Global Burden of Disease (GBD) database, relevant data of hip and knee OA in five East Asian countries from 1990 to 2023 (170 country-year observations in total) were extracted. Descriptive analysis, correlation analysis, and ARIMA prediction model were used to analyze the association between Socio-Demographic Index (SDI) and disease burden indicators (DALYs rate, prevalence rate, incidence rate).
resultsThe disease burden in high-SDI countries was significantly higher than that in low-SDI countries (Japan's DALYs rate, 59.32 per 100,000 population; Mongolia's DALYs rate, 22.45 per 100,000 population, P < 0.001). There was a strong positive correlation between SDI and DALYs rate (r = 0.726; 95% CI, 0.631-0.805). Females (DALYs rate, 45.23 per 100,000 population in 2023) and the 40-49 age group were high-risk populations.
conclusionThe disease burden of hip and knee OA in East Asia is significantly correlated with the level of socioeconomic development. It is essential to formulate differentiated prevention and control strategies for countries with different SDI levels to reduce the population's disease burden. Key Points • First systematic analysis of hip and knee osteoarthritis disease burden in five East Asian countries from 1990 to 2023, revealing a strong positive correlation with the Socio-Demographic Index (SDI) • Identified females and the 40-49 age group as high-risk, with disease burden growth significantly faster in low-SDI countries than high-SDI ones • Proposed differentiated prevention strategies: elderly rehabilitation in high-SDI, addressing urban-rural disparities in mid-SDI, and enhancing diagnostic capacity in low-SDI countries • Provided data support for public health policy and medical resource allocation for osteoarthritis in East Asia.
Indexed as
Identifiers
41820754What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.